Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description does disclose useful behavior: the result includes abstracts for every term and `terms` are kept in the given order. However, it does not explicitly state that the operation is read-only, what happens when neither or both inputs are supplied, or how invalid topics are handled.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is short and front-loads the returned value before explaining inputs. The trailing reference to a selection on alexjung.at/baukasten/ is somewhat cryptic and adds little for an agent.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no annotations, no output schema, and 0% schema description coverage, it covers the return content and both parameters reasonably well. It remains incomplete on tool-selection guidance and edge-case behavior, which matter for correct invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, so the description properly carries the burden: it explains `topic` as a path id or words from the title or audience, and `terms` as an explicit ordered list of term keys or names. It still does not clarify mutual exclusivity or precedence if both are provided.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States that the tool returns one reading order together with the abstract of every term in it, which is specific enough to understand the resource and result. It only implicitly distinguishes itself from list_learning_paths by saying 'one reading order' rather than a list.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explains how to choose between `topic` and `terms`, but gives no guidance on when to use this tool instead of siblings such as list_learning_paths, lookup_term, or search_terms. The alternatives and selection conditions are left to inference.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.